Metamaterial enhanced sensor for powder material classification

In this paper, a simple and efficient approach is presented to classify different power materials based on a one port microwave sensor in X-band. This classification focuses on powder materials, unlike prior studies that focused on liquids (castor oil, neem oil, sunflower oil, sesame oil, and mahua oil), this classification represents a shift towards powdered materials. The response of the proposed sensor is enhanced by adding a metamaterial (MTM) unit cell of F-shape to focus electromagnetic waves on the sample under test. This metamaterial-based sensor is designed to differentiate between different types of materials based on the corresponding reflection coefficient. The sample under test is included inside a dielectric box inserted inside a rectangular waveguide. The MTM unit cell is added on the front face of this box towards the direction of the incident wave. The resonance frequency depends on the characteristics of the powder material inside the box. The MTM unit cell enhances this resonance to simplify the process of classification of different materials. The measured results show that the proposed sensor can detect a wide range of powder materials, including clay, cement, sand, and mixtures: cement & sand, and clay & sand. The designed sensor can be used in various applications, including detection and classification of different powder materials in industrial applications.

field distribution.Partial removal of the dielectric substrate creates a cavity below the stub, forming a sensitive region for sample interaction.Introducing a liquid or material within this cavity modifies the effective permittivity experienced by the stub, leading to a shift in the cavity resonator's resonant frequency due to altered modal characteristics.
Zhang et al. introduced a microwave metamaterial absorber specifically designed for non-destructive sensing in the grain industry, potentially improving efficiency and minimizing waste within the agricultural and food sectors 21 .Islam et al. developed a metamaterial sensor using a unique star-enclosed split ring resonator design.This sensor effectively detects adulteration in gasoline and oil 22 .The research by Yu et al. explores a new application to act as sensors for terahertz metamaterial absorbers.This dual functionality is particularly attractive for compact or integrated systems 23 .The liquid or solid sample under test (SUTs) can then be placed in the container, which is sandwiched between the chiral metamaterial structures.Alternatively, the SUTs can be positioned at the front or back of the metamaterial sensing surface.This can be achieved by placing the SUTs in a waveguide adjuster, which serves as a holder for the SUTs 24 .A star-shaped, dual-band (C and X band) tunable microwave sensor designed for high-performance sensing of both solid and liquid materials, including FR-4 substrates, Rogers laminates (RO3035, RO5880, RT6202), and various liquids (milk, oil, water, and even an energy drink).The metamaterial array and its liquid reservoir positioned between the waveguide structures, eliminating the need for complete enclosure within the waveguide cavity 25 .A key feature of waveguide sensor topology is the use of chiral metamaterials.These materials strategically arrange resonators in an asymmetric manner, leading to unique benefits for sensor performance 26 .To achieve negative refraction more efficiently, the design utilizes resonators with chiral asymmetry.These resonators reside on opposing sides of the substrate and exhibit a geometry that prevents perfect mirroring.This configuration offers additional advantages through mutual coupling effects 27 .One example of this concept is the use of split-ring resonators (SRRs) in these double-sided chiral structures 28 .
MTM sensors have emerged applications in various fields, including biological and medical diagnostics, agricultural monitoring, and environmental sensing [29][30][31] .This paper presents a sensor based on one-port waveguide with a modified F-shape unit cell to classify different powder in X band.The paper is organized as follows: Section "Design of metamaterial unit cell sensor" introduces the unit cell sensor design.Section "Equivalent circuit of the F-shape unit cell sensor" equivalent circuit and field distribution.Section "Analysis and design of F-shape sensor inside WG" operation of one-port waveguide sensors with MTM unit cell.Finally, conclusion is presented in Section "Conclusion".

Design of metamaterial unit cell sensor
The numerical studies of the F-shaped resonator are designed and analyzed using finite element method (FEM) based HFSS software.The proposed sensor design operates in the X-band frequency regime.The dimensions of unit cell are adjusted to fill the waveguide section WR-90 with inner dimensions 22.86 × 10.16 mm 2 , as shown in Fig. 1.This size selection facilitates compatibility with an X-band waveguide for experimental work using the waveguide measurement method.To determine the optimal dimensions for the proposed unit cell sensor, a parametric analysis is performed to be suitable for the analysis in the frequency region from 9 to 11 GHz.The top and the bottom layers of the MTM unit cell are illustrated in Fig. 1b and c.This unit cell is printed on FR4 www.nature.com/scientificreports/dielectric substrate with a dielectric constant ε r = 4.3 and loss tangent tan δ = 0.02.The substrate thickness is 1.6 mm. Figure 2, shows the reflection and transmission coefficients of this unit cell.The equivalent metamaterial characteristics of this unit cell can be obtained by using the resulting complex reflection and transmission coefficients as follows 32 : The effective parameters (ε, μ, n and z) are shown in Fig. 3a-c.It can be noted that negative real permittivity for this unit cell lies in the frequency ranges from 9.785 GHz to 10.3 GHz and 10.66 GHz to 10.96 GHz.On the other hand, negative real permeability lies in the frequency ranges from 10.3 GHz to 10.44 GHz and 10.52 GHz to 10.71 GHz.Negative real refractive index is observed over the frequency ranges from 9.96 GHz to 10.43 GHz and 10.55 GHz to 10.95 GHz.

Equivalent circuit of the F-shape unit cell sensor
The equivalent circuit of the designed F-shape unit cell sensor is shown in Fig. 4a.The unit cell can be divided into five parts such as TL1, TL2, TL3, G1, and G2 as shown in Fig. 4b.
Transmission lines inherently introduce inductive effects due to their physical characteristics.These effects can be defined as L1, L2, L3 respectively.The presence of a gap is equivalent to C1 and C2 which correspond to the capacitive coupling between the conductors.The unit cell's behavior can be accurately modeled using an RLC circuit, as illustrated in Fig. 4a.
The impedance of the F-shape unit cell sensor is defined as Refs. 33,34ere Z t , R t , L t , C t are respectively denoting the total impedance, total resistance, total inductance and total capacitance of the unit cell structure.The resonance frequency is given by Refs. 33,34e performance of the unit cell by using HFSS and the corresponding equivalent circuit by using ADS is shown in Fig. 5. Table 1, presents the different components values of the equivalent circuit.www.nature.com/scientificreports/by using Dielectric Assessment Kite (DAK) are listed in Table 2.These values are used in the present study to introduce the simulation results for the proposed sensor to discriminate between these different materials.These simulation results are verified experimentally to introduce the applicability of this sensor for fast discrimination between these materials.The proposed materials are mainly used in civil engineering.Thus, it is expected that this simple sensor can be quite useful for onsite tests for civil engineering.Figures 7 and 8 illustrate, respectively, the electric field and surface current distributions within the sand sample at the resonant frequency of 10.48 GHz. Figure 7 highlights how, for air, the electric field primarily concentrates near the resonator's surface.While electromagnetic fields can travel through conductive cables, the field within the sensor is expected to be in the Transverse Electromagnetic (TEM) mode.This mode dictates that the electric field component is zero.Analyzing the distributions of both the electric field and surface current is crucial to comprehend the underlying theory of the sensor's design.These distributions offer insights into the energy storage and loss mechanisms within the device, as changes in these fields reveal information about the contained energy and any energy dissipation.

Analysis and design of F-shape sensor inside WG
The distribution of surface currents flowing along the edges of the F-shaped sensor at its resonant frequency of 10.48 GHz (when a sand sample is present), as shown in Fig. 8. Red arrows visualize the direction of current flow.The currents are strongest and most concentrated at the top and bottom of the sensor, flowing in clockwise and counter-clockwise directions.

Experimental verification
The measured and simulated reflection coefficient for the proposed unit cell inside WG is shown in Fig. 10.It can be noted that there is a good agreement between the measured and simulated results.However, little fabrication and calibration errors introduce minor discrepancies between them.Significant noise observed in the results, due to fabrication and calibration tolerances produce some minor performance variations.The proposed setup for powder material classification is shown in Fig. 11.When designing an effective sensor to distinguish among powder samples, the frequency band should be carefully determined because the dielectric permittivity depends on the frequency.The network analyzer and dielectric probe kit which are used to measure the dielectric permittivity of the samples are adjusted to be in the frequency range from 8 to12 GHz.
During the measurements, certain oscillatory fluctuations were detected on the VNA.These fluctuations are attributed to the combined effects of waveguide coupling and MTM sensor fabrication tolerances within the prototype FR-4 substrate layer.Fluctuations were additionally influenced by the dielectric properties of the substrate and environmental factors affecting the measurement.
Figure 12 illustrates the simulated and experimental results for reflection coefficients of different powder samples.It can be noted that experimental results align with the numerical study.It is concluded that from these figures without MTM structure, there were no transition in the resonance frequency for different powder samples which leads to difficulty in the classification process.On the other hand, using MTM unit cell introduces different resonance frequencies for powder samples.This can be explained due to the field enhancement by the MTM unit cell which acts as a lens for electromagnetic waves, focusing them onto the sample under test.This concentrated energy makes it easier to distinguish between different samples based on their interactions with the incident waves.
Table 3 shows the responses of reflection coefficients for different powder samples with/without the MTM structure.

Comparison with other related works
The proposed sensor performance metrics, including frequency band, material under test, sensing parameters, and resonant frequency shift, are compared with those of established microwave sensors documented in the literature, as shown in Table 4. Unlike other microwave sensors which are developed to measure liquid materials based on both S11 and/or S21 response, the present sensor is used to classify powder samples by analyzing S11 only with frequency shifts ranging from 30 to 60 MHz between different samples.

Conclusion
This paper presents modified F-shaped unit cell sensor for the classification of various powder materials based on a one-port waveguide measurement.The classification performance of various powder samples was compared with and without the use of an MTM structure by using HFSS.The frequency-shifting property allows the sensor to achieve high sensitivity in distinguishing between different samples.The dimensions of the designed sensor are 22.86 × 10.16 mm 2 , making it perfectly compatible with X-band waveguide dimensions.The equivalent circuit of the F-shape unit cell sensor was studied by using ADS.The proposed sensor utilizes frequency shifting to achieve precise discrimination between various samples.The simulation and experimental results demonstrate that the presence of an MTM structure significantly enhances the classification accuracy for different powder samples.The recommended sensor can be used in various applications, including the detection of powder materials and industrial applications.

Figure 6
Figure 6 shows the configuration of the proposed sensor for classifying powder materials.It consists of a unit cell of metamaterial embedded inside on the open end of a rectangular waveguide.The powder material is placed in dielectric container attached to the open end of the waveguide.The sample container is a hollow cube of outer

21 Fig. 2 .
Fig.2.Simulated reflection and transmission coefficients for the proposed MTM structure.

Fig. 3 .
Fig. 3. (a) Relative permittivity for the proposed MM structure (b) Relative permeability for the proposed MM structure (c) Refractive index for the proposed MM structure.

Figure 9 ,
shows the reflection coefficient for different powder samples without the MTM unit cell and with MTM unit cell.It can be noted that the MTM unit cell enhances the discrimination between different samples by introducing sharp clear different resonances for these different materials.The obtained resonance frequencies with MTM are 9.82 GHz, 9.92 GHz and 10.22 GHz for the cement with sand, clay and sand with − 26.53 dB, − 25.95 dB and -24.78 dB magnitude, respectively.Whereas, for cement and clay with sand, the magnitude values are − 26.03 dB at 10.42 GHz and − 23.33 dB at 10.66 GHz, respectively.

Table 1 .
Values of different components of the Equivalent circuit.

Table 2 .
Measured average dielectric constant ( ε r ) and Tan δ of powder materials under test.

Table 3 .
Comparison for different samples with/without the MTM structure.

Table 4 .
Comparative evaluation of performance Metrics: Our Work versus previous work.